{"id":"W4319082079","doi":"10.26685/urncst.426","title":"Feasibility Study: Machine Learning in Neurodegenerative Disorders, Alzheimer’s Disease","year":2023,"lang":"en","type":"article","venue":"Undergraduate Research in Natural and Clinical Science and Technology (URNCST) Journal","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Artificial intelligence; Machine learning; Logistic regression; Medical diagnosis; Binary classification; Computer science; Clinical decision support system; Support vector machine; Medicine; Decision support system; Pathology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01582755,0.0003927993,0.0003857113,0.0008249006,0.0005228359,0.001079339,0.000838626,0.0007980103,0.007075865],"category_scores_gemma":[0.03987813,0.0001998005,0.0005367602,0.001046185,0.000517038,0.001618708,0.001367593,0.000967056,0.001382909],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006875274,"about_ca_system_score_gemma":0.003590505,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002353186,"about_ca_topic_score_gemma":0.0026002,"domain_scores_codex":[0.9948967,0.003273023,0.000228727,0.0003806593,0.001050821,0.0001699885],"domain_scores_gemma":[0.9713455,0.020337,0.0009353456,0.001656453,0.004784304,0.0009412353],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.007463519,0.007393304,0.4686156,0.001696665,0.0004389462,0.0008450402,0.0008572817,0.01126201,0.005105034,0.007404248,0.01243006,0.4764883],"study_design_scores_gemma":[0.003862306,0.05207323,0.5796127,0.001757144,0.0009246027,0.004276676,0.003803256,0.2612206,0.02378003,0.03046303,0.03800514,0.000221372],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9300746,0.002262874,0.04271345,0.006904591,0.0003381094,0.005963852,0.002932583,0.0003405676,0.008469276],"genre_scores_gemma":[0.9539462,0.0006035303,0.03931497,0.0006111543,0.0001032906,0.002000645,0.001692728,0.00002000117,0.001707502],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01582755,"threshold_uncertainty_score":0.08370507,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.336305018328938,"score_gpt":0.5862845611743495,"score_spread":0.2499795428454115,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}